Magnetic resonance imaging
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To develop a fast and accurate convolutional neural network based method for segmentation of thalamic nuclei. ⋯ The proposed segmentation method is fast, accurate, performs well across disease types and field strengths, and shows great potential for improving our understanding of thalamic nuclei involvement in neurological diseases.
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Arterial spin labeling MRI can quantify the cerebral blood flow (CBF) without exogenous tracer. However, the variation of arterial transit time across different brain regions introduces bias for measuring local CBF, especially for those subjects with long arterial transit time (ATT). Long post-labeling delay (PLD) or multi-PLD methods could mitigate the problem of heterogenous ATT at the expense of the signal-to-noise ratio (SNR). Long-label ASL might address the low SNR problem by increasing the amount of labeled arterial blood. Thus, we hypothesized that with the same relatively long PLD, long-label pCASL may be more robust and reproducible than standard-label pCASL in population with potentially prolonged ATT. The purpose of the study was to investigate the reliability and reproducibility of long-label pCASL in the whole brain and vascular regions of interest in an elderly population, compared with standard-label pCASL. ⋯ The study demonstrated good reliability and reproducibility of long-label pCASL in anterior brain regions in the elderly population. To further improve CBF quantification in a long-ATT population while proper PLD is already used, increasing the label duration may help.
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The osteochondral junction (OCJ) of the knee joint is comprised of multiple tissue components, including a portion of the deep layer cartilage, calcified cartilage, and subchondral bone. The OCJ is of increasing radiological interest as it may be relevant in the early pathogenesis of osteoarthritis (OA). Due to its short transverse relaxation, the OCJ is invisible to clinical MR sequences. ⋯ Representative T1-weighted FS-UTE-Cones images of the whole knee of a healthy volunteer showed high signal intensity bands in the OCJ regions of the patella, femur, and tibia. On the other hand, T1-weighted FS-UTE-Cones imaging of the knee joints of OA patients revealed regions with reduction or loss of these high signal intensity bands in the OCJ regions, indicating abnormal OCJ tissue composition. The proposed 3D T1-weighted FS-UTE-Cones sequence with a 3-min scan time may be very useful for demonstrating the involvement of the OCJ regions in early OA.
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Comparative Study
Absolute quantification of cerebral blood flow: correlation between dynamic susceptibility contrast MRI and model-free arterial spin labeling.
To compare absolute cerebral blood flow (CBF) estimates obtained by model-free arterial spin labeling (ASL) and dynamic susceptibility contrast MRI (DSC-MRI), corrected for partial volume effects (PVEs). ⋯ A satisfactory positive linear correlation between the CBF estimates obtained by model-free ASL and DSC-MRI was observed, and DSC-to-ASL CBF ratios showed no obvious tissue dependence.
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Subject motion during MRI scan can result in severe degradation of image quality. Existing motion correction algorithms rely on the assumption that no information is missing during motions. However, this assumption does not hold when out-of-FOV motion happens. Currently available algorithms are not able to correct for image artifacts introduced by out-of-FOV motion. The purpose of this study is to demonstrate the feasibility of incorporating convolutional neural network (CNN) derived prior image into solving the out-of-FOV motion problem. ⋯ In conclusion, the proposed CNN-based motion correction algorithm can significantly reduce out-of-FOV motion artifacts and achieve better image quality compared to AF-based algorithm.